PHOENIX creates a private industrial intelligence environment that connects physical asset evidence to production demand, maintenance execution and capacity. Local models, AgentSWARMS, CIP, contextual memory, reporting and app-building tools turn that context into decisions that protect throughput and revenue.
Enterprise GPU compute, memory and fast local storage sized for private model inference and engineering workloads.
Critical Infrastructure Protection — the plant security and access layer controlling what AI can read, which tools it can use and what can leave the site.
The on-prem intelligence workspace where multiple local models, agents, contextual memory, reports, coding tools and domain knowledge work together.
Approved connectivity to DCS, PLC, historians, CMMS, ERP, databases, engineering files, Git and APIs.
Initial on-site support for configuration, model/RAG setup, agent creation, testing, optimization and user training.
Your competitive advantage is not just a motor waveform. It is the combination of operations, maintenance, engineering knowledge, production context, recipes, work history and machine data. On-prem AI lets you use that combined knowledge without making the public cloud your plant's primary intelligence layer.
Sensitive plant information, documents, embeddings, RAG indexes and model workloads can remain inside the customer's own network.
AI can connect asset condition, maintenance, production, engineering, logistics and commercial priorities to understand what actually limits reliable capacity.
Models do not receive unrestricted network access. CIP controls the identities, tools, credentials, sources and actions permitted for each agent.
Domain experts can create reusable agents, Python or HTML apps, reports, analytics and decision logic while the knowledge and history remain on-prem.
PHOENIX works with the customer to size and deploy the on-prem compute platform required for local model inference, plant data access, RAG, engineering agents, coding and analytics.
A typical starting deployment combines enterprise GPU compute, ECC memory, mirrored NVMe storage, Linux, containerized inference services, LabSource and PHOENIX CIP.
Customer infrastructure: customer provides the approved rack/location, network connection, UPS/power and suitable cooling/environment. Facility electrical work, rack changes and dedicated HVAC/cooling are excluded unless separately scoped.
Launch support: LabSource / PHOENIX can provide an on-site FTE for the first month, renewable monthly, to configure the environment, set up models/RAG/agents, optimize performance, test workflows and train users.
The PHOENIX AI stack is strongest when it has access to high-quality physical data from the assets themselves. PHOENIX combines autonomous sensing, long-range wireless connectivity and high-resolution vibration analytics to create a continuously available asset-health data layer.
Capture machine behavior at the level required for real rotating-equipment diagnostics, not just simple threshold alarms.
Create a persistent digital health layer across critical assets so condition data becomes part of the wider operational and maintenance context.
Extend low-power wireless sensing across industrial facilities without the cost and complexity of wiring every monitored point.
The value is not the sensor alone and it is not the LLM alone. The advantage comes from binding physical asset evidence to maintenance, operations, production and engineering context, then letting local AI reason across the combined picture.
High-resolution vibration, airflow, pressure, oil quality, temperature, speed and other asset-health signals create a trusted machine-state record.
PHOENIX CIP securely connects approved maintenance, process, production, historian, controls, CMMS, ERP and engineering sources to that asset evidence.
LabSource runs local models and specialized agents that can correlate machine behavior with operating state, work history, procedures, drawings and other approved context.
Engineers can turn recurring analysis into reusable agents, dashboards, calculations, reports, alerts and local applications without sending the plant's full knowledge base to the cloud.
Instead of asking a generic model “what does this vibration peak mean?”, LabSource can evaluate the vibration against actual RPM, load, VFD frequency, maintenance history, oil condition, machine geometry, process state and recent operating changes.
Use local coding agents to build plant-specific calculations, workflows, connectors, dashboards, reports and decision modules. The code can work directly with approved internal data sources through CIP-controlled tools.
PHOENIX connects machine evidence, maintenance, operations, planning and local AI differently for each industry — with the same goal: protect reliable capacity, production commitments and revenue.
Drills, draglines, haul trucks, leach pads and distributed mine operations — connecting equipment health to tons moved, process availability and production value at risk.
Paper machines, drives, gearboxes, fans, pumps and process systems — connecting reliability and operating context to sustained machine speed, quality and mill throughput.
Critical Infrastructure Protection, local AI and asset intelligence for generation facilities — protecting availability while keeping AI access governed, auditable and separated from direct plant control.
Two different on-prem layers with two very different jobs: CIP controls access to the plant. LabSource is where the AI reasons, analyzes and builds.
PHOENIX CIP — Critical Infrastructure Protection — is the secure industrial access and governance layer between AI and your plant systems.
It controls what AI can see, which systems and tools it can use, which credentials it can access, whether an action is read-only or write-enabled, and what information is allowed to leave the facility.
In simple terms: CIP is the security and control boundary for industrial AI.
LabSource is the customer’s private AI Factory — the on-prem workspace where local LLMs, agents, RAG, coding and analytics run.
LabSource uses the approved context CIP makes available and helps engineers analyze problems, ask questions of plant data, generate reports, write code, build agents and create new industrial applications.
In simple terms: LabSource is where the AI thinks, analyzes and builds.
The AI server is the physical compute platform that runs LabSource, PHOENIX CIP and the local models. It provides the GPU, memory and storage needed to keep industrial AI inference and plant intelligence inside the customer environment.
The server is the engine room.
The Asset Health Sensor Network provides the physical evidence: high-resolution vibration, pressure, airflow, oil quality, temperature, speed and other machine-health data. Long-range Bluetooth and gateways move that evidence into the PHOENIX environment.
The sensor network tells the AI what the machines are actually doing.
PHOENIX UI is the enterprise decision layer that connects the truth of what is happening in the plant with work execution, energy burden, lifecycle cost and capital planning.
LabSource and PHOENIX CIP create the secure on-prem intelligence foundation. PHOENIX UI turns that intelligence into an operating and capital decision framework that plant managers, reliability teams, maintenance leaders and executives can use together.
PHOENIX UI helps answer three practical questions:
PHOENIX connects asset sensing, plant context and local AI around the operating realities of heavy industry.
Condition intelligence, long-range BLE and local AI across distributed mining assets and operations.
Asset-health and AI intelligence built against production process, operations, logistics constraints and available mill capacity.
PHOENIX is designed to answer a bigger question than “is this machine healthy?” It connects what the business must produce, the condition of the assets required to produce it, the work needed to keep them available, and the operational constraints that determine how much capacity can actually be committed with confidence.
Product mix, grade, orders, production schedule, throughput targets and required capacity define the business demand on the plant.
Condition data, vibration, oil, pressure, temperature, alarms and operating history show which equipment threatens the production plan.
Process state, operating conditions, changeovers, recipes, historian data, staffing, outages and other context explain what is happening around the asset.
PMs, work orders, inspections, maintenance history, spare parts and engineering recommendations show what intervention is needed and when.
Parts, labor, contractor access, materials, transport, inventory, crane access, shutdown windows and other constraints determine whether the plan is practical.
PHOENIX connects the evidence so teams can prioritize work, protect throughput, estimate reliable capacity and focus attention where production commitments or revenue are most exposed.
LabSource builds the context for each question from approved internal information. The intelligence is used to support planning, engineering, reliability and maintenance integration — not to directly control equipment.
Product, grade, throughput, line speed, schedule, orders, operating targets and capacity requirements.
Condition monitoring, sensor evidence, operating state, failure history and asset hierarchy.
PM schedules, CMMS work orders, inspections, repair history, labor requirements and maintenance backlog.
Parts availability, inventory, supplier lead time, material movement, access, contractors and execution constraints.
Drawings, manuals, BOMs, SOPs, prior investigations, code, calculations and engineering decisions.
Past events, chats, retrieved evidence, model requests, expert corrections, decisions, production losses and maintenance outcomes remain attached to the work and strengthen future reasoning.
How high-resolution machine evidence becomes capacity intelligence when it is connected to maintenance, operating context and the production requirement.
Learn MoreHow CIP governs tools, credentials, data access and controlled cloud exchange.
Learn MoreLocal LLMs, RAG, engineering agents, coding and application development.
Learn MoreDeploy a private industrial intelligence environment that connects machine evidence, plant systems, domain expertise and local AI to the production plan — so reliability, operations, maintenance and management can work from the same view of reliable capacity and revenue at risk.
